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The ongoing digital revolution has pushed banks in reinventing their business models. It has led to a significant rise of distributed technology consumerism. Beyond the walls of testing standalone smarter devices, web applications and more, the needle has shifted towards envisioning outcome-driven frictionless user journeys. This indicates the wider scope of digital quality engineering in today’s experience centric economy.

In order to provide the right consumer experience, the software development process has gone through a significant transformation, and along with that adopting DevOps or Dev-Sec-Ops culture has prioritized concepts that support continuous integration and continuous delivery to maintain continuous quality. AI led test automation practices can speed up the launch of your digital initiatives.

We have come a fair distance from the  first wave of test automation tools (WinRunner, Silk Test and QTP) or even the second wave (Industry’s erstwhile favourite, Selenium), and to the exciting cognitive world of AI or ML tools.

Before diving into the specifics and features of AI tools, it is prudent to ask: Why AI?

Digital Quality Engineering involves various tasks – manual testing, scripted automated testing, and non-functional testing. What AI testing does well, is that it adds value to the existing testing effort by auto exploring apps and critical features on the real devices. This ensures all the existing functionality and user flow works perform as normal.

Additionally, AI testing assists if there are any new bugs or issues introduced while exploring the app. Frequently QA teams use AI testing tools to supplement their testing efforts in addition to normal digital testing tasks like manual, exploratory or scripted automation testing. AI engineering recently featured among the top technology trends for 2021 as predicted by Gartner.

In sum, leveraging AI-powered testing tools in today’s digital testing landscape, helps organizations achieve largest test coverage in limited time with never-seen accuracy. And this is where the equation, saved time + money = faster time to market, makes business sense.

Now to some of the popular Industry offerings and more importantly the features that differentiate.

Testcraft, Applitools, Functionize, Sauce Labs, Sealights, Test.AI, Mabl, ReTest, ReportPortal and Testim – make up the list of the best-acknowledged test automation tools, that leverage AI and ML to speed up the authoring, execution and maintenance of automated tasks.

Most of them are Cloud based, and support a comprehensive list of browsers and operating systems, mobile emulators, and simulators and digital devices.  Each one has their strengths – A few come with adaptive algorithms that are able to modify their comparison algorithms to discern what changes are meaningful and/or noticeable and then there are other test automation tools that eliminates flaky tests by continuously comparing test results to test history to quickly detect regressions, resulting in more stable releases.

From a testing organizational point of view, if we cherry pick techno-business features that distinguishes AI led digital quality engineering model from traditional models, then the following checklist are likely to emerge.

  • Shrinks testing cycle times like getting 500 API’s validated in a minute
  • Power of codeless test automation which doesn’t require coding knowledge
  • Vast device and platform coverage through cloud based solutions lab which offers multitude of devices, browsers, OS etc
  • Large scale testing productivity improvement opportunities through early bug prevention and course corrections
  • Envision customer journey outcomes by identifying critical user scenarios and regression tests
  • Using AI based mobile testing solutions which provides comprehensive coverage for exploratory testing
  • AI led testing solutions enacts feedback mechanisms based on history of failures and issues detected and resolved.
  • Flexibilities of platform agnosticism – be it on SaaS, Cloud, On-Premise, and hybrid environment
  • Energised CI/CD pipelines for maintaining continuous quality

Maveric’s Digital Quality Engineering proficiency empanels an AI based platform for embracing continuous quality. Digital testing will have no hope if it rides on traditional and manual approaches in the current age of speed. Businesses need intelligent approaches with the right digital QE mastery and real time insight driven dashboards, that uniquely anticipate typical pitfalls and proactively manage the choke points through various contextual solutions. Digital QE empanelled with AI powered levers will help banking businesses to maintain continuous quality with superior experience journeys.

Article by

Rajesh Vasudevan

Vice President and Client Partner